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Tool for statistical evaluation of the simulation process of JSimlib4 library
Pivoda, Štefan ; Míča, Ivan (referee) ; Burget, Radim (advisor)
This master's thesis deals with the analysis of simulation of computer networks. A statistical tool was designed for evaluating a communication between stations in the computer network. JSimlib4 Java library was used for the simulation of computer networks. It is a lightweight but robust simulation library, designed for creating simple or even quite complex simulation models of distributed systems. The Statistical tool was written in Java programming language and developed in an EasyEclipse integrated development environment. It was designed as an Eclipse Rich Client Platform application. Eclipse Rich Client Platform is a relatively new technology, which has a lot of favorable properties. The Statistical tool can be divided into 3 parts: • creating a log file, • creating a filter, • creating/showing an output. The Statistical tool creates records into a log file during every communication between stations. This log file contains a comment on the first line. This comment describes the definition of records. Every record contains 2 IP addresses with the used ports at the beginning of the record, then the time, the amount of bytes, the protocol and the direction of communication. Every item in the record is divided by a colon. The Statistical tool can evaluate a communication between stations. At first, it has to define a filter according to which it will assess the suitable stations. It can be created either by adding IP addresses or names of the stations onto a list on a workbench. Filter can be loaded from a file that already includes these IP addresses and other information too. After defining the filter, the Statistical tool can create either a diagram or a file. At first, the Statistical tool reads the log file line by line and compares the IP addresses, which were added to the filter with the IP addresses in a log file. When the Statistical tool finds a complying IP address, it reads the whole line and adds an amount of bytes defined on that line to the final diagram that is shown after reading the whole log file. In the case of finding 2 or more complying IP addresses that sent the data at the same time, an amount of these transfers is calculated by adding them and this amount is then shown in a diagram. After reading the whole log file a diagram or a file is shown at the bottom of the window. The diagram is created by a Java library JFreechart and it shows the amount of transferred bytes. The x-axis represents the time and the y-axis represents the amount of transferred bytes. The created file is for next work with the calculated data and it can be loaded for example by Matlab or Octave. The first line in the file represents the time for axis x and the second one represents the amount of transferred bytes for axis y. These lines are followed by a command "plot(x,y)" for drawing a diagram.
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SW support for emotional state analysis
Lněnička, Jakub ; Míča, Ivan (referee) ; Smékal, Zdeněk (advisor)
The goal of my bachelor work is the description of SW tool with the graphic interface which can be made use of for the purpose of developing the multimodal emotional databases. In its beginning my work deals with the description of the parts of the human body that produce voice (vocal cords) and their functioning. The text is a description of the procedure of transferring the human voice into the digital form where a special attention is paid to the parameters of the speech signal with the emphasis on the description of the symptoms that serve to the purpose of defining the chosen emotions. This work deals with the categorization of emotions and the description of some of them. In the closing part the K-NN classificator is described that serves to the recognition of the individual feelings by means of a produced software.
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Comparison of success rate of multi-channel methods of speech signal separation
Přikryl, Petr ; Zezula, Radek (referee) ; Míča, Ivan (advisor)
The separation of independent sources from mixed observed data is a fundamental problem in many practical situations. A typical example is speech recordings made in an acoustic environment in the presence of background noise or other speakers. Problems of signal separation are explored by a group of methods called Blind Source Separation. Blind Source Separation (BSS) consists on estimating a set of N unknown sources from P observations resulting from the mixture of these sources and unknown background. Some existing solutions for instantaneous mixtures are reviewed and in Matlab implemented , i.e Independent Componnent Analysis (ICA) and Time-Frequency Analysis (TF). The acoustic signals recorded in real environment are not instantaneous, but convolutive mixtures. In this case, an ICA algorithm for separation of convolutive mixtures in frequency domain is introduced and in Matlab implemented. This diploma thesis examines the useability and comparisn of proposed separation algorithms.
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Decoder for key word detection system
Krotký, Jan ; Míča, Ivan (referee) ; Pfeifer, Václav (advisor)
The essay presents the basic characteristics of human speech recognition, describes systems for the detection of key words and further deals with the proposal of each decoder blocks divided into three chapters. The first one describes the operations that are performed before the signal distribution of the framework and the segmentation. The second chapter describes the calculation of short-term energy, the number of zero passes and self-correlative, prediction and Mel-frequency cepstral coefficients. The third chapter, which describes the design of the block decoder, describes the method of dynamic time destruction and the method based on hidden Markov model. The final part of the essay describes decoders working with a speech and a proposal for a simple decoder working with isolated words, which was based issued and tested based on the preceding chapters.
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Noise Source Identification Using Beamforming
Kurc, David ; Míča, Ivan (referee) ; Schimmel, Jiří (advisor)
This master's thesis is focused on the noise source identification using microphone arrays and beamforming as the signal processing method. It describes parts of such a system and provides a comparison with other systems that serve a similar purpose (eg. NAH). Various types of microphone arrays are mentioned with their influence on the resulting ability to identify the noise source. We are further focusing on Delay-And-Sum technology, on which we are explaining the basic principles and constraints of beamforming. The practical part describes the implementation of the DAS method in MATLAB and C language, the specific structures of built microphone arrays and assembly of complete systems capable of identifying sources of noise. These systems were tested by performing a practical experiment. Achievements in the form of distribution maps of acoustic energy in the focused space are interpreted in the last chapter.
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Comparison of voice and audio codecs
Lúdik, Michal ; Sysel, Petr (referee) ; Míča, Ivan (advisor)
This thesis deals with description of human hearing, audio and speech codecs, description of objective measure of quality and practical comparison of codecs. Chapter about audio codecs consists of description of lossless codec FLAC and lossy codecs MP3 and Ogg Vorbis. In chapter about speech codecs is description of linear predictive coding and G.729 and OPUS codecs. Evaluation of quality consists of description of segmental signal-to- noise ratio and perceptual evaluation of quality – WSS and PESQ. Last chapter deals with description od practical part of this thesis, that is comparison of memory and time consumption of audio codecs and perceptual evaluation of speech codecs quality.
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Assessment of diffusion coefficient
Mikeš, Petr ; Schimmel, Jiří (referee) ; Míča, Ivan (advisor)
Most acoustic measurements and parameters provided by a manufacturer of acoustic elements, which are offering additional solutions to room acoustics as well as acoustic construction works, are mainly limited to the parameters associated with absorption of individual elements. Until now, these diffusional elements have been neglected. Diffusi- onal panels are used to e.g. eliminate direct reflection of sound waves to the listener or reflection of sound waves concentrated at one point. Combination of absorptive acoustic panels and diffusion elements results in a space that is customised to the submitter’s needs.
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Implemetation of algorithms for blind source separation in C/C++ language
Funderák, Marcel ; Malý, Jan (referee) ; Míča, Ivan (advisor)
This thesis is describing one of the methods of Blind Source Separation (BSS) which is Independent Component Analysis. There is shown some brief introduction to the theory behind in which there are explained some basic findings. These findings are important for understanding the theory behind algorithms of ICA. These theoretical findings include primarily explanations of basic knowledge of statistics science. In next part there are described methods which are advisable for preprocessing of input signals – mainly Principal Component Analysis (PCA) and whitening of signals. Mainly whitening is very important part of solution of ICA algorithms. Then there are described different ICA algorithm solutions and especially introduction in this problematic. FastICA algorithm description is mainly depicted because it is very good for computer processing since it is strong and it is less computer demanding than other algorithms. After that follows implementation of one of the ICA algorithm in C++ programming language. FastICA algorithm for complex valued signal was chosen.
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Statical acoustical sources localization
Mikeš, Petr ; Holešinský, Pavel (referee) ; Míča, Ivan (advisor)
The microphone array can be used in many important applications. The primary usage, which most of other applications are based on, is only: acoustic sources localization and separation of each signal from their compound. The microphone array is usually included in ordinary mobile phones, where it reduces noise and sound of its surrounding that otherwise degrades vocal speech. Other microphone array utilization is in for example speech identification, speakers’ localization or signal isolation of one speaker.
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